As these results show mainly countries with a huge surface, we want to put the increase of reforestation from 1990-2020 in relation to the forest area in 1990.
(source of idea https://plotly.com/r/choropleth-maps/#introduction-main-parameters-for-choropleth-outline-maps)
First of all we want to show the relation of total reforestation and deforestation in the last 30 years, to get a first glimpse.
As there are many outliers with either very high deforestation/reforestation figures, we can zoom in by changing the scale.
The figure shows already a high and not linear distrubtion of our data.
With the Shapiro-Wilk test we want to show the normality of our data.
##
## Shapiro-Wilk normality test
##
## data: corref$totalref
## W = 0.25387, p-value < 2.2e-16
##
## Shapiro-Wilk normality test
##
## data: corref$totaldef
## W = 0.16293, p-value < 2.2e-16
The values are below 0.05 for both, reforestation and deforestation, the data significantly deviate from a normal distribution. A result which was already highlited by the graph.
As the data is therefore not linear, we should choose the Spearman method to calculate the correlation.
## # A tibble: 2 x 3
## term totalref totaldef
## <chr> <dbl> <dbl>
## 1 totalref NA 0.206
## 2 totaldef 0.206 NA
##
## Pearson's product-moment correlation
##
## data: corref$totalref and corref$totaldef
## t = 3.2181, df = 234, p-value = 0.001473
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.08027866 0.32502440
## sample estimates:
## cor
## 0.2058687
## # A tibble: 2 x 3
## term totalref totaldef
## <chr> <dbl> <dbl>
## 1 totalref NA 0.451
## 2 totaldef 0.451 NA
##
## Spearman's rank correlation rho
##
## data: corref$totalref and corref$totaldef
## S = 1201838, p-value = 3.009e-13
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## 0.4513834
However with 0.451 it doesn’t show a significant correlation, which means, at least in the last 30 years, countries did not really try “to make up” for a human driven deforestation.